Uncertainty-dependent data collection in vehicular sensor networks

Abstract

Vehicular sensor networks (VSNs) are built on top of vehicular ad-hoc networks (VANETs) by equipping vehicles with sensing devices. These new technologies create a huge opportunity to extend the sensing capabilities of the existing road traffic control systems and improve their performance. Efficient utilisation of wireless communication channel is one of the basic issues in the vehicular networks development. This paper presents and evaluates data collection algorithms that use uncertainty estimates to reduce data transmission in a VSN-based road traffic control system.

10 pages, 6 figures

References in corpus (6)

• Cellular Automata Models of Road Traffic
• Self-Control of Traffic Lights and Vehicle Flows in Urban Road Networks
• Selective data collection in vehicular networks for traffic control applications
• Performance Evaluation of Road Traffic Control Using a Fuzzy Cellular Model
• Fuzzy cellular model for on-line traffic simulation
• Fuzzy cellular model of signal controlled traffic stream

Cited by in corpus (4)

• Uncertainty-based information extraction in wireless sensor networks for control applications
• Optimizing data collection for object tracking in wireless sensor networks
• Communication-aware algorithms for target tracking in wireless sensor networks
• Data Suppression Algorithms for Surveillance Applications of Wireless Sensor and Actor Networks